Current robotic systems are incapable of fully characterizing their interaction with the environment. Full characterization of the interaction means: discerning collisions, localizing contact constraints, and estimating interaction forces. Although there are mature algorithms for compliant hybrid motion/force control, there exists no unified framework for the impact and post-impact phases. These algorithms require a priori knowledge of the environmental constraint geometry via formulation of natural and artificial constraints or motion and constraint screws. Previous works on rigid-link robots do not apply directly to continuum manipulators and do not provide a unified method for both collision detection and estimation of contact location without a priori knowledge of the environmental constraints and additional sensory devices such as robotic skins.
Previous works individually focused on collision detection, and estimation of constraint locations. For example, generalized momentum of serial robots was used to identify contact incidence and the link at which contact occurs. Additionally, a least-squares method using an estimate of contact location from tactile sensors and joint torque measurements to estimate the magnitude and the location of contact force was presented. Further, two different probabilistic approaches for contact estimation were proposed. Still other researchers have tried to overcome the limitations of rigid-link robots by developing sensitive robotic skins.
Continuum robots are continuously bending, infinite-degree-of-freedom elastic structures that offer an opportunity to overcome the limitations of rigid-link robots. This opportunity stems from the ability of continuum robots to change their shape when interacting with the environment.
The motivation behind investigation into methods for robot manipulation originates in the field of medical robotics. New surgical paradigms such as Natural Orifice Transluminal Endoscopic Surgery (NOTES) demand deeper anatomical reach along increasingly tortuous paths. Medical robots need to be intelligent to autonomously prevent inadvertent trauma to surrounding anatomy while accomplishing surgical tasks beyond the capabilities of conventional robotic platforms for Minimally Invasive Surgery (MIS) in order to meet the challenges of NOTES. Further, robots need to support automated or semi-automated insertion into the anatomy, regulate their contact forces along the whole structure, and use their multi-point interactions to enhance end-effector precision. Up until now, several researchers have relied on passive compliance of continuum robots and wire-actuated articulated robots. However, reliance on passive compliance of surgical robots comes with a price of performance degradation such as payload carrying capability and position accuracy.